Abstract: Methods and apparatuses for dynamically budgeting power usage in a data processing system. In one aspect, a data processing system, includes: one or more components including a first component; and a computing element, such as a microprocessor or a microcontroller, coupled to the first component to obtain one or more operating signals from the first component and to determine, based at least in part on the one or more operating signals, an estimate of a power consumption requirement of the one or more components for operating under the current condition. In one example, one or more sensors are used to determine information on actual power usage for a past period of time. A performance level setting of a second component, such as a CPU, a GPU, or a bus, is determined using the estimate and the information on the actual power usage, such as the operating voltage and frequency.

Abstract: Methods and apparatuses to dynamically manage a performance state of a data processing system are described. The data processing system includes a plurality of components; one or more buses coupled to the plurality of components, and a dynamic performance state manager unit coupled to the components. The dynamic performance state manager unit is configured to receive information about a first plurality of current states of components of the system. The dynamic performance state manager unit is configured to determine a second plurality of required system performance states for the components; and to determine a current system performance state based on the first plurality and the second plurality.

Abstract: Methods and apparatuses to manage working states of a data processing system. At least one embodiment of the present invention includes a data processing system with one or more sensors (e.g., physical sensors such as tachometer and thermistors, and logical sensors such as CPU load) for fine grain control of one or more components (e.g., processor, fan, hard drive, optical drive) of the system for working conditions that balance various goals (e.g., user preferences, performance, power consumption, thermal constraints, acoustic noise). In one example, the clock frequency and core voltage for a processor are actively managed to balance performance and power consumption (heat generation) without a significant latency. In one example, the speed of a cooling fan is actively managed to balance cooling effort and noise (and/or power consumption).

Abstract: A method and apparatus for detecting and identifying the attributes of level-2 (L2) memory cache modules in a computer system. An ID Module is attached to each L2 cache memory module containing memory attribute information such as size, presence or absence of parity, synchronous or asynchronous access ability, electrical timing, etc. The information is accessible using a parallel or serial interface.